1. Why is data quality and consistency so important for AI in construction?

AI only works as well as the data it learns from—and in construction, that data is often messy, old or misleading.

Key issues with historical data:

• Up to 80% of past schedules are considered “garbage data” (tender drafts, what-if scenarios, or outdated versions)
• Lack of consistent naming, formatting, or structures between projects and teams
• Data that doesn’t reflect on-site reality

How to fix it:

• Adopt tools like Asta Vision to structure and standardise data at source 
• Use global code libraries and approval workflows to maintain quality 
• Make sure project data reflects real progress, not just idealised plans 

Without clean, consistent data, AI and machine learning can’t offer reliable predictions or insight.

2. What role does Asta Vision play in a modern planning data strategy? 

Asta Vision is more than a data repository—it’s a system for turning inconsistent project data into a strategic asset. 

It helps teams: 

• Centralise all project data in one platform 

• Standardise naming, workflows, and program structures 

• Create collaborative sign-off and approval workflows 

• Track schedule health and project stages in real-time 

• Enable comparison across sectors, regions, and project types 

When data is structured and accessible, you’re able to unlock consistent, cross-portfolio reporting and set the stage for future AI use. 

3. How does Acumine Build Intelligence™ enhance what Asta Vision does? 

Acumine builds on the foundation set by Asta Vision by transforming your data into rich, visual, actionable dashboards using Microsoft Fabric and Power BI. 

With Acumine, you can: 

• Get instant visibility across all projects in a portfolio 

• Drill down from KPI-level dashboards into individual project performance 

• View critical path tracking, milestone variance, WIP trends, and more 

• Integrate other data sources (commercial, safety, quality) for deeper insight 

In short, Asta Vision gets your project data clean and Acumine makes it more usable across teams, projects and portfolios. 

4. What are the biggest productivity blockers in construction today? 

The industry’s productivity problem isn’t just a matter of effort—it’s systemic. 

Current challenges include: 

• Optimism bias in scheduling to win bids 

• Increasing project complexity and difficulty assessing risk 

• Reduced workforce experience due to a shrinking talent pool 

• Disconnected tools and limited visibility across functions 

AI has the potential to help, but only when organisations commit to better data practices through standardisation. 

5. Is BIM data vital for AI-driven planning? 

While Gantt charts are helpful, they lack the richness and relevance needed for accurate AI forecasting. BIM (Building Information Modelling) adds the detail required for smarter predictions. 

BIM data gives AI: 

• Real-world context on objects, sequencing, and dependencies 

• Spatial insights that improve activity duration estimates 

• Opportunities to link planning with commercial, quality, or safety data 

By combining BIM with planning data, organisations can create a far more intelligent dataset for scenario planning and predictive analytics. 

6. What’s required to start using dashboards like Acumine’s? 

You don’t need to be “data-mature” to begin. In fact, the act of reporting is what helps uncover problems and improve quality. 

Here’s what you need to get started: 

• A baseline schedule to measure against 

• Regular progress updates (weekly is ideal) 

• Centralised data in Asta Vision or Powerproject 

• The confidence to start—even if it’s messy 

As soon as you start using the data, you’ll begin to see where improvements are needed. 

7. How can companies kickstart their data and AI journey? 

Start simple. Start now. 

The best way to begin is: 

• Use your data to build a few dashboards, even basic ones 

• Let reporting expose any issues with consistency or structure 

• Standardise naming and workflows across teams 

• Record progress against a reliable baseline 

Over time, this creates a dataset that is fit for AI, and a reporting culture that drives continuous improvement. 

8. Will AI replace planners and schedulers? 

Not anytime soon—and likely never completely. 

AI will: 

• Take over repetitive, low-value tasks 

• Help planners identify risk earlier 

• Run complex scenario modelling 

• Free up time for strategic, creative thinking 

But human expertise is still essential. The role of the planner is evolving, not disappearing. 

Final Thoughts 

AI and data-driven decision-making aren’t some distant vision—they’re already here and happening now. But success depends on building a solid foundation of clean, structured data as well as consistent workflows across teams. 

Platforms like Asta Vision and Acumine Build Intelligence™ are helping construction leaders gain the visibility, confidence, and control they need to deliver projects and portfolios smarter, faster, and with greater foresight. 

If you missed the webinar, you can watch on demand here:  

https://elecosoft.com/events/transforming-planning-data-into-portfolio-intelligence-with-elecosoft-and-acumine/